init

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,90 @@
+import torch
+import system
+from utils import load_cfg
+
+from PIL import Image
+import torchvision.transforms as transforms
+import gradio as gr
+from torchvision.transforms import v2
+
+
+import wandb
+
+cfg = load_cfg("configs/effb0-base-breakhis.yaml")
+
+model = system.SimpleClassificationSystem.load_from_checkpoint(
+    "runs/03_20_2025_20_19_28/wandb/histopath/03_20_2025_20_19_28/checkpoints/epoch=210-step=41778.ckpt",
+    torch.device("cpu"),
+    cfg=cfg.system
+)
+
+model.to("cuda")
+model.eval()
+
+print("Model loaded successfully!")
+
+image_size = cfg.data.image_size
+
+def preprocess_image(image: Image):
+    '''Preprocess the image to be compatible with the model'''
+    transform = transforms.Compose([
+        v2.Resize(image_size, antialias=True),
+        v2.PILToTensor(),
+        v2.ToDtype(torch.float32, scale=True),
+        v2.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
+    ])
+    
+    return transform(image).unsqueeze(0).to("cuda")
+
+
+def predict(image_path: str):
+    '''Predict the class of the image'''
+
+    image = Image.open(image_path).convert("RGB")
+
+    image = preprocess_image(image)  
+    with torch.no_grad():
+        output = model(image)  
+        output = output.squeeze()  
+        pred = torch.sigmoid(output).round()  
+        return f"Predicted Class: {'Benign' if int(pred.item())==0 else 'Malignant'}"
+
+examples = [
+    "examples/breakhis/benign/adenosis/SOB_B_A-14-22549AB-40-001.png",
+    "examples/breakhis/benign/adenosis/SOB_B_A-14-22549AB-100-001.png",
+    "examples/breakhis/benign/adenosis/SOB_B_A-14-22549AB-200-013.png",
+    "examples/breakhis/benign/adenosis/SOB_B_A-14-22549AB-400-006.png",
+    "examples/breakhis/benign/fibroadenoma/SOB_B_F-14-9133-40-001.png",
+    "examples/breakhis/benign/fibroadenoma/SOB_B_F-14-9133-100-010.png",
+    "examples/breakhis/benign/fibroadenoma/SOB_B_F-14-9133-200-011.png",
+    "examples/breakhis/benign/fibroadenoma/SOB_B_F-14-9133-400-006.png",
+    "examples/breakhis/malignant/ductal/SOB_M_DC-14-2523-40-010.png",
+    "examples/breakhis/malignant/ductal/SOB_M_DC-14-2523-100-024.png",
+    "examples/breakhis/malignant/ductal/SOB_M_DC-14-2523-200-027.png",
+    "examples/breakhis/malignant/ductal/SOB_M_DC-14-2523-400-013.png",
+    "examples/breakhis/malignant/lobular/SOB_M_LC-14-12204-40-002.png",
+    "examples/breakhis/malignant/lobular/SOB_M_LC-14-12204-100-031.png",
+    "examples/breakhis/malignant/lobular/SOB_M_LC-14-12204-200-031.png",
+    "examples/breakhis/malignant/lobular/SOB_M_LC-14-12204-400-034.png"
+]
+
+examples_labels = ["benign"] * 8 + ["malignant"] * 8
+
+examples_with_labels = [[example, label] for example, label in zip(examples, examples_labels)]
+
+# Gradio Interface
+interface = gr.Interface(
+    fn=predict, 
+    inputs=gr.Image(type="filepath", label="Upload an image"),  
+    outputs=gr.Label(),  
+    live=True,
+    examples=examples_with_labels,
+    title="Histopathology Image Classification",
+    description="This application classifies histopathology images as either benign or malignant. Upload an image to get the prediction.",
+    examples_per_page=len(examples_with_labels),
+)
+
+gr.DeepLinkButton()
+
+if __name__ == "__main__":
+    interface.launch(share=True)

configs/effb0-base-breakhis.yaml

@@ -0,0 +1,79 @@
+name: effb0-base-breakhis
+save_dir: runs
+trial_dir: ${get_trial_dir:${save_dir}}
+save_cfg_path: ${path_append:${trial_dir},config.yaml}
+seed: 0
+
+data_type: BreakhisDataModule
+data:
+  data_source: /home/duong/Downloads/BreaKHis_v1/histology_slides/breast
+  batch_size: 32
+  shuffle: ${get_shuffle:${train.trainer.devices}}
+  num_workers: 8
+  image_size: [224, 224]
+  aug:
+    RandomHorizontalFlip: 
+      p: 0.2
+    RandomVerticalFlip:
+      p: 0.2
+    RandomRotation:
+      degrees: [-5, 5]
+    # GaussianNoise:
+    #   p: 0.2
+    ColorJitter:
+      brightness: 0.5
+      contrast: 0.5
+    
+
+system_type: SimpleClassificationSystem
+system:
+  model_type: TimmModel
+  model:
+    model_name: efficientnet_b0
+    pretrained: true
+    num_classes: 1
+  optimizer:
+    name: Adam
+    args:
+      lr: 1.e-3
+  scheduler:
+    name: CosineAnnealingLR
+    args:
+      T_max: ${train.trainer.max_epochs}
+  loss: 
+    name: BCEWithLogitsLoss
+  metrics:
+    metrics_names: [BinaryAccuracy]
+    metrics_short_names: [BA]
+
+train:
+  trainer:
+    accelerator: 'gpu'
+    devices: [0]
+    max_epochs: 300
+    check_val_every_n_epoch: 1
+    enable_progress_bar: true
+    accumulate_grad_batches: 1
+    log_every_n_steps: 50
+    default_root_dir: ${trial_dir}
+  logger:
+    names: [WandbLogger, CSVLogger]
+    args:
+       wandb:
+         name: ${get_run_id:${trial_dir}}
+         project: histopath
+         save_dir: ${path_append:${trial_dir},wandb}
+         id: ${get_run_id:${trial_dir}}
+         anonymous: false
+         log_model: all
+         entity: heartbeats
+       csv:
+          name: csv
+          save_dir: ${trial_dir}
+  callback:
+    names: [ModelCheckpoint]
+    args:
+      modelcp:
+        save_last: true
+        monitor: valid/BA
+        mode: max

configs/effb0-base-camelyon.yaml

@@ -0,0 +1,68 @@
+name: effb0-base-camelyon
+save_dir: runs
+trial_dir: ${get_trial_dir:${save_dir}}
+save_cfg_path: ${path_append:${trial_dir},config.yaml}
+seed: 0
+
+data_type: CamelyonDataModule
+data:
+  data_source: /mnt/local-vision/quanda12/projects/DomainBed/domainbed/data
+  train_path: ${path_append:${data.data_source},train}
+  valid_path: ${path_append:${data.data_source},val}
+  test_path: ${path_append:${data.data_source},test}
+  batch_size: 4096
+  shuffle: ${get_shuffle:${train.trainer.devices}}
+  num_workers: 3
+  image_size: [96, 96]
+
+system_type: SimpleClassificationSystem
+system:
+  model_type: TimmModel
+  model:
+    model_name: efficientnet_b0
+    pretrained: true
+    num_classes: 1
+  optimizer:
+    name: Adam
+    args:
+      lr: 1.e-3
+  scheduler:
+    name: CosineAnnealingLR
+    args:
+      T_max: ${train.trainer.max_epochs}
+  loss: 
+    name: BCEWithLogitsLoss
+  metrics:
+    metrics_names: [BinaryAccuracy, BinaryF1Score, BinaryPrecision, BinaryRecall]
+    metrics_short_names: [BA, BF1, BP, BR]
+
+train:
+  trainer:
+    accelerator: 'gpu'
+    devices: [2]
+    max_epochs: 10
+    check_val_every_n_epoch: 1
+    enable_progress_bar: true
+    accumulate_grad_batches: 1
+    log_every_n_steps: 50
+    default_root_dir: ${trial_dir}
+  logger:
+    # names: [WandbLogger, CSVLogger]
+    names: [CSVLogger]
+    args:
+      # wandb:
+      #   name: ${get_run_id:${trial_dir}}
+      #   project: histpath
+      #   save_dir: ${path_append:${trial_dir},wandb}
+      #   id: ${get_run_id:${trial_dir}}
+      #   anonymous: false
+      #   log_model: all
+      csv:
+        name: csv
+        save_dir: ${trial_dir}
+  callback:
+    names: [ModelCheckpoint]
+    args:
+      modelcp:
+        monitor: valid/BA
+        mode: max

configs/effb0-scratch.yaml

@@ -0,0 +1,68 @@
+name: effb0-scratch
+save_dir: runs
+trial_dir: ${get_trial_dir:${save_dir}}
+save_cfg_path: ${path_append:${trial_dir},config.yaml}
+seed: 0
+
+data_type: BaseDataModule
+data:
+  data_source: /media/mountHDD1/users/luffy/data/oral-cancer-hhp
+  train_path: ${path_append:${data.data_source},train}
+  valid_path: ${path_append:${data.data_source},val}
+  test_path: ${path_append:${data.data_source},test}
+  batch_size: 32
+  shuffle: ${get_shuffle:${train.trainer.devices}}
+  num_workers: 3
+  image_size: [224, 224]
+
+system_type: SimpleClassificationSystem
+system:
+  model_type: TimmModel
+  model:
+    model_name: efficientnet_b0
+    pretrained: true
+    num_classes: 1
+  optimizer:
+    name: Adam
+    args:
+      lr: 5.e-4
+  scheduler:
+    name: CosineAnnealingLR
+    args:
+      T_max: ${train.trainer.max_epochs}
+  loss: 
+    name: BCEWithLogitsLoss
+  metrics:
+    metrics_names: [BinaryAccuracy, BinaryF1Score, BinaryPrecision, BinaryRecall]
+    metrics_short_names: [BA, BF1, BP, BR]
+
+train:
+  trainer:
+    accelerator: 'gpu'
+    devices: [1]
+    max_epochs: 100
+    check_val_every_n_epoch: 1
+    enable_progress_bar: true
+    accumulate_grad_batches: 1
+    log_every_n_steps: 50
+    default_root_dir: ${trial_dir}
+  logger:
+    # names: [WandbLogger, CSVLogger]
+    names: [CSVLogger]
+    args:
+      # wandb:
+      #   name: ${get_run_id:${trial_dir}}
+      #   project: histpath
+      #   save_dir: ${path_append:${trial_dir},wandb}
+      #   id: ${get_run_id:${trial_dir}}
+      #   anonymous: false
+      #   log_model: all
+      csv:
+        name: csv
+        save_dir: ${trial_dir}
+  callback:
+    names: [ModelCheckpoint]
+    args:
+      modelcp:
+        monitor: valid/BA
+        mode: max

models/__init__.py

@@ -0,0 +1 @@
+from .timm_model import TimmModel

models/timm_model.py

@@ -0,0 +1,30 @@
+from torch import nn
+from dataclasses import dataclass, field
+from utils import parse_structure
+
+import timm
+
+@dataclass
+class TimmModelConfig:
+    model_name: str = 'efficientnet_b0'
+    pretrained: bool = True
+    num_classes: int = 1
+
+class TimmModel(nn.Module):
+    cfg: TimmModelConfig
+    def __init__(self, cfg: TimmModelConfig) -> None:
+        super(TimmModel, self).__init__()
+        
+        self.cfg = parse_structure(TimmModelConfig, cfg)
+        self.model_name = self.cfg.model_name
+        self.pretrained = self.cfg.pretrained
+        self.num_classes = self.cfg.num_classes
+
+        self.model = timm.create_model(
+            model_name=self.model_name, 
+            pretrained=self.pretrained,
+            num_classes=self.num_classes
+        )
+
+    def forward(self, x):
+        return self.model(x)

runs/03_20_2025_20_19_28/check_onnx.txt

@@ -0,0 +1,39 @@
+malignant - benign - -4.33505392074585 - 0.012931746648633455 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/fibroadenoma/SOB_B_F_14-21998CD/400X/SOB_B_F-14-21998CD-400-002.png
+malignant - benign - -5.0183424949646 - 0.006572005831300832 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/fibroadenoma/SOB_B_F_14-14134/100X/SOB_B_F-14-14134-100-021.png
+malignant - benign - -4.308588027954102 - 0.013273962400185626 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/fibroadenoma/SOB_B_F_14-14134/400X/SOB_B_F-14-14134-400-034.png
+malignant - benign - 0.7163642048835754 - 0.6718058883186611 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/fibroadenoma/SOB_B_F_14-14134/200X/SOB_B_F-14-14134-200-030.png
+malignant - benign - -4.19320821762085 - 0.014873217736598748 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/fibroadenoma/SOB_B_F_14-14134/200X/SOB_B_F-14-14134-200-034.png
+malignant - benign - -2.4580321311950684 - 0.0788531555727457 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/fibroadenoma/SOB_B_F_14-23222AB/400X/SOB_B_F-14-23222AB-400-013.png
+malignant - benign - -3.5009539127349854 - 0.02928510123260563 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/fibroadenoma/SOB_B_F_14-23222AB/400X/SOB_B_F-14-23222AB-400-016.png
+malignant - benign - 3.9832870960235596 - 0.9817162045476688 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/fibroadenoma/SOB_B_F_14-14134E/100X/SOB_B_F-14-14134E-100-025.png
+malignant - benign - 3.8090155124664307 - 0.9783108539445998 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/fibroadenoma/SOB_B_F_14-25197/100X/SOB_B_F-14-25197-100-002.png
+malignant - benign - -4.11960506439209 - 0.01599106160349348 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/fibroadenoma/SOB_B_F_14-25197/100X/SOB_B_F-14-25197-100-031.png
+malignant - benign - 3.016782522201538 - 0.9533265723803946 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/fibroadenoma/SOB_B_F_14-25197/100X/SOB_B_F-14-25197-100-024.png
+malignant - benign - -4.029786109924316 - 0.017467590973030852 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/fibroadenoma/SOB_B_F_14-25197/100X/SOB_B_F-14-25197-100-018.png
+malignant - benign - 4.73707914352417 - 0.9913119361675163 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/fibroadenoma/SOB_B_F_14-25197/40X/SOB_B_F-14-25197-40-032.png
+malignant - benign - -2.0689001083374023 - 0.11215651623167847 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/fibroadenoma/SOB_B_F_14-25197/400X/SOB_B_F-14-25197-400-035.png
+malignant - benign - 5.976008892059326 - 0.9974674906090553 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/fibroadenoma/SOB_B_F_14-25197/200X/SOB_B_F-14-25197-200-044.png
+malignant - benign - -4.534403324127197 - 0.01061932907616857 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/fibroadenoma/SOB_B_F_14-25197/200X/SOB_B_F-14-25197-200-039.png
+malignant - benign - -3.760202646255493 - 0.022749437815595772 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/fibroadenoma/SOB_B_F_14-29960AB/40X/SOB_B_F-14-29960AB-40-011.png
+malignant - benign - -5.58329439163208 - 0.003746071839190041 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/tubular_adenoma/SOB_B_TA_14-3411F/100X/SOB_B_TA-14-3411F-100-001.png
+malignant - benign - 4.587532043457031 - 0.9899246007392932 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/tubular_adenoma/SOB_B_TA_14-3411F/40X/SOB_B_TA-14-3411F-40-003.png
+malignant - benign - -3.814971923828125 - 0.02156311801735704 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/tubular_adenoma/SOB_B_TA_14-3411F/400X/SOB_B_TA-14-3411F-400-016.png
+malignant - benign - 9.489089965820312 - 0.9999243327890416 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/tubular_adenoma/SOB_B_TA_14-16184CD/100X/SOB_B_TA-14-16184CD-100-003.png
+malignant - benign - -5.953848361968994 - 0.002589110676997338 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/tubular_adenoma/SOB_B_TA_14-16184CD/400X/SOB_B_TA-14-16184CD-400-022.png
+malignant - benign - -3.6893680095672607 - 0.024378621250484518 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/tubular_adenoma/SOB_B_TA_14-21978AB/100X/SOB_B_TA-14-21978AB-100-011.png
+malignant - benign - -1.7499383687973022 - 0.14805497169615128 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/tubular_adenoma/SOB_B_TA_14-16184/40X/SOB_B_TA-14-16184-40-003.png
+malignant - benign - -5.737329006195068 - 0.003213009671732214 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/tubular_adenoma/SOB_B_TA_14-13200/40X/SOB_B_TA-14-13200-40-010.png
+malignant - benign - 4.169759750366211 - 0.9847792780965864 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/adenosis/SOB_B_A_14-22549AB/40X/SOB_B_A-14-22549AB-40-025.png
+malignant - benign - -0.8399221301078796 - 0.30155118455021834 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/adenosis/SOB_B_A_14-22549AB/400X/SOB_B_A-14-22549AB-400-017.png
+malignant - benign - -5.662906169891357 - 0.0034603948919703117 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/adenosis/SOB_B_A_14-22549AB/200X/SOB_B_A-14-22549AB-200-009.png
+malignant - benign - -3.4140844345092773 - 0.03185817914785674 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/adenosis/SOB_B_A_14-22549G/40X/SOB_B_A-14-22549G-40-016.png
+malignant - benign - 0.5923433899879456 - 0.6439026473476818 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/adenosis/SOB_B_A_14-22549G/40X/SOB_B_A-14-22549G-40-025.png
+malignant - benign - -3.1917922496795654 - 0.039475765930985326 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/adenosis/SOB_B_A_14-22549G/200X/SOB_B_A-14-22549G-200-004.png
+malignant - benign - -4.041451930999756 - 0.017268499589852174 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/phyllodes_tumor/SOB_B_PT_14-21998AB/40X/SOB_B_PT-14-21998AB-40-057.png
+malignant - benign - -5.547115802764893 - 0.00388354490088842 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/phyllodes_tumor/SOB_B_PT_14-21998AB/40X/SOB_B_PT-14-21998AB-40-003.png
+malignant - benign - -1.3316751718521118 - 0.20888240714803552 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/phyllodes_tumor/SOB_B_PT_14-21998AB/400X/SOB_B_PT-14-21998AB-400-034.png
+malignant - benign - 2.14650559425354 - 0.895341786102712 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/phyllodes_tumor/SOB_B_PT_14-21998AB/400X/SOB_B_PT-14-21998AB-400-037.png
+malignant - benign - -4.412107944488525 - 0.011984219294003636 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/phyllodes_tumor/SOB_B_PT_14-21998AB/400X/SOB_B_PT-14-21998AB-400-014.png
+malignant - benign - -4.79934549331665 - 0.008167871708461739 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/phyllodes_tumor/SOB_B_PT_14-21998AB/400X/SOB_B_PT-14-21998AB-400-053.png
+malignant - benign - -5.051648139953613 - 0.006358094627719743 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/phyllodes_tumor/SOB_B_PT_14-29315EF/400X/SOB_B_PT-14-29315EF-400-003.png
+malignant - benign - -5.201243877410889 - 0.005479516229230595 - /home/duong/Downloads/BreaKHis_v1/histology_slides/breast/benign/SOB/phyllodes_tumor/SOB_B_PT_14-29315EF/200X/SOB_B_PT-14-29315EF-200-012.png

runs/03_20_2025_20_19_28/config.yaml

@@ -0,0 +1,83 @@
+name: effb0-base-breakhis
+save_dir: runs
+trial_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_20_2025_20_19_28
+save_cfg_path: /home/duong/Github_repos/Histopathology_Project/runs/03_20_2025_20_19_28/config.yaml
+seed: 0
+data_type: BreakhisDataModule
+data:
+  data_source: /home/duong/Downloads/BreaKHis_v1/histology_slides/breast
+  batch_size: 32
+  shuffle: true
+  num_workers: 8
+  image_size:
+  - 224
+  - 224
+  aug:
+    RandomHorizontalFlip:
+      p: 0.2
+    RandomVerticalFlip:
+      p: 0.2
+    RandomRotation:
+      degrees:
+      - -5
+      - 5
+    ColorJitter:
+      brightness: 0.5
+      contrast: 0.5
+system_type: SimpleClassificationSystem
+system:
+  model_type: TimmModel
+  model:
+    model_name: efficientnet_b0
+    pretrained: true
+    num_classes: 1
+  optimizer:
+    name: Adam
+    args:
+      lr: 0.001
+  scheduler:
+    name: CosineAnnealingLR
+    args:
+      T_max: 300
+  loss:
+    name: BCEWithLogitsLoss
+  metrics:
+    metrics_names:
+    - BinaryAccuracy
+    metrics_short_names:
+    - BA
+train:
+  trainer:
+    accelerator: gpu
+    devices:
+    - 0
+    max_epochs: 300
+    check_val_every_n_epoch: 1
+    enable_progress_bar: true
+    accumulate_grad_batches: 1
+    log_every_n_steps: 50
+    default_root_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_20_2025_20_19_28
+  logger:
+    names:
+    - WandbLogger
+    - CSVLogger
+    args:
+      wandb:
+        name: '03_20_2025_20_19_28'
+        project: histopath
+        save_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_20_2025_20_19_28/wandb
+        id: '03_20_2025_20_19_28'
+        anonymous: false
+        log_model: all
+        entity: heartbeats
+      csv:
+        name: csv
+        save_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_20_2025_20_19_28
+  callback:
+    names:
+    - ModelCheckpoint
+    args:
+      modelcp:
+        save_last: true
+        monitor: valid/BA
+        mode: max

runs/03_20_2025_20_19_28/csv/version_0/metrics.csv

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runs/03_28_2025_00_21_48/config.yaml

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+name: effb0-base-breakhis
+save_dir: runs
+trial_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_00_21_48
+save_cfg_path: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_00_21_48/config.yaml
+seed: 0
+data_type: BreakhisDataModule
+data:
+  data_source: /home/duong/Downloads/BreaKHis_v1/histology_slides/breast
+  batch_size: 32
+  shuffle: true
+  num_workers: 8
+  image_size:
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+    pretrained: true
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+  optimizer:
+    name: Adam
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+  scheduler:
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+  loss:
+    name: BCEWithLogitsLoss
+  metrics:
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+    - BinaryAccuracy
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+    - BA
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+    check_val_every_n_epoch: 1
+    enable_progress_bar: true
+    accumulate_grad_batches: 1
+    log_every_n_steps: 50
+    default_root_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_00_21_48
+  logger:
+    names:
+    - WandbLogger
+    - CSVLogger
+    args:
+      wandb:
+        name: '03_28_2025_00_21_48'
+        project: histopath
+        save_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_00_21_48/wandb
+        id: '03_28_2025_00_21_48'
+        anonymous: false
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+        entity: heartbeats
+      csv:
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+        save_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_00_21_48
+  callback:
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+    - ModelCheckpoint
+    args:
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+        monitor: valid/BA
+        mode: max

runs/03_28_2025_00_32_51/config.yaml

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+name: effb0-base-breakhis
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+save_cfg_path: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_00_32_51/config.yaml
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+  data_source: /home/duong/Downloads/BreaKHis_v1/histology_slides/breast
+  batch_size: 32
+  shuffle: true
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+    name: BCEWithLogitsLoss
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+    - BinaryAccuracy
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+    - BA
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+    enable_progress_bar: true
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+    default_root_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_00_32_51
+  logger:
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+    - WandbLogger
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+        name: '03_28_2025_00_32_51'
+        project: histopath
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+        anonymous: false
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+        entity: heartbeats
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+        save_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_00_32_51
+  callback:
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+    - ModelCheckpoint
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+        mode: max

runs/03_28_2025_00_35_19/config.yaml

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+seed: 0
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+  data_source: /home/duong/Downloads/BreaKHis_v1/histology_slides/breast
+  batch_size: 32
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+  - 224
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+      - 5
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+  loss:
+    name: BCEWithLogitsLoss
+  metrics:
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+    - BinaryAccuracy
+    metrics_short_names:
+    - BA
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+    - 0
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+    enable_progress_bar: true
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+    default_root_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_00_35_19
+  logger:
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+    - WandbLogger
+    - CSVLogger
+    args:
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+        name: '03_28_2025_00_35_19'
+        project: histopath
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+  callback:
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+    - ModelCheckpoint
+    args:
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+        mode: max

runs/03_28_2025_01_36_41/config.yaml

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+  data_source: /home/duong/Downloads/BreaKHis_v1/histology_slides/breast
+  batch_size: 32
+  shuffle: true
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+  image_size:
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+  - 224
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+  loss:
+    name: BCEWithLogitsLoss
+  metrics:
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+    - BA
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+    default_root_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_01_36_41
+  logger:
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+        name: '03_28_2025_01_36_41'
+        project: histopath
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+        save_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_01_36_41
+  callback:
+    names:
+    - ModelCheckpoint
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+        mode: max

runs/03_28_2025_01_56_02/config.yaml

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+    - BA
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+  callback:
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+    - ModelCheckpoint
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+        name: '03_28_2025_01_58_16'
+        project: histopath
+        save_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_01_58_16/wandb
+        id: '03_28_2025_01_58_16'
+        anonymous: false
+        log_model: all
+        entity: heartbeats
+      csv:
+        name: csv
+        save_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_01_58_16
+  callback:
+    names:
+    - ModelCheckpoint
+    args:
+      modelcp:
+        save_last: true
+        monitor: valid/BA
+        mode: max

runs/03_28_2025_01_58_52/config.yaml

@@ -0,0 +1,83 @@
+name: effb0-base-breakhis
+save_dir: runs
+trial_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_01_58_52
+save_cfg_path: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_01_58_52/config.yaml
+seed: 0
+data_type: BreakhisDataModule
+data:
+  data_source: /home/duong/Downloads/BreaKHis_v1/histology_slides/breast
+  batch_size: 32
+  shuffle: true
+  num_workers: 8
+  image_size:
+  - 224
+  - 224
+  aug:
+    RandomHorizontalFlip:
+      p: 0.2
+    RandomVerticalFlip:
+      p: 0.2
+    RandomRotation:
+      degrees:
+      - -5
+      - 5
+    ColorJitter:
+      brightness: 0.5
+      contrast: 0.5
+system_type: SimpleClassificationSystem
+system:
+  model_type: TimmModel
+  model:
+    model_name: efficientnet_b0
+    pretrained: true
+    num_classes: 1
+  optimizer:
+    name: Adam
+    args:
+      lr: 0.001
+  scheduler:
+    name: CosineAnnealingLR
+    args:
+      T_max: 300
+  loss:
+    name: BCEWithLogitsLoss
+  metrics:
+    metrics_names:
+    - BinaryAccuracy
+    metrics_short_names:
+    - BA
+train:
+  trainer:
+    accelerator: gpu
+    devices:
+    - 0
+    max_epochs: 300
+    check_val_every_n_epoch: 1
+    enable_progress_bar: true
+    accumulate_grad_batches: 1
+    log_every_n_steps: 50
+    default_root_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_01_58_52
+  logger:
+    names:
+    - WandbLogger
+    - CSVLogger
+    args:
+      wandb:
+        name: '03_28_2025_01_58_52'
+        project: histopath
+        save_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_01_58_52/wandb
+        id: '03_28_2025_01_58_52'
+        anonymous: false
+        log_model: all
+        entity: heartbeats
+      csv:
+        name: csv
+        save_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_01_58_52
+  callback:
+    names:
+    - ModelCheckpoint
+    args:
+      modelcp:
+        save_last: true
+        monitor: valid/BA
+        mode: max

runs/03_28_2025_02_00_29/config.yaml

@@ -0,0 +1,83 @@
+name: effb0-base-breakhis
+save_dir: runs
+trial_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_00_29
+save_cfg_path: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_00_29/config.yaml
+seed: 0
+data_type: BreakhisDataModule
+data:
+  data_source: /home/duong/Downloads/BreaKHis_v1/histology_slides/breast
+  batch_size: 32
+  shuffle: true
+  num_workers: 8
+  image_size:
+  - 224
+  - 224
+  aug:
+    RandomHorizontalFlip:
+      p: 0.2
+    RandomVerticalFlip:
+      p: 0.2
+    RandomRotation:
+      degrees:
+      - -5
+      - 5
+    ColorJitter:
+      brightness: 0.5
+      contrast: 0.5
+system_type: SimpleClassificationSystem
+system:
+  model_type: TimmModel
+  model:
+    model_name: efficientnet_b0
+    pretrained: true
+    num_classes: 1
+  optimizer:
+    name: Adam
+    args:
+      lr: 0.001
+  scheduler:
+    name: CosineAnnealingLR
+    args:
+      T_max: 300
+  loss:
+    name: BCEWithLogitsLoss
+  metrics:
+    metrics_names:
+    - BinaryAccuracy
+    metrics_short_names:
+    - BA
+train:
+  trainer:
+    accelerator: gpu
+    devices:
+    - 0
+    max_epochs: 300
+    check_val_every_n_epoch: 1
+    enable_progress_bar: true
+    accumulate_grad_batches: 1
+    log_every_n_steps: 50
+    default_root_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_00_29
+  logger:
+    names:
+    - WandbLogger
+    - CSVLogger
+    args:
+      wandb:
+        name: '03_28_2025_02_00_29'
+        project: histopath
+        save_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_00_29/wandb
+        id: '03_28_2025_02_00_29'
+        anonymous: false
+        log_model: all
+        entity: heartbeats
+      csv:
+        name: csv
+        save_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_00_29
+  callback:
+    names:
+    - ModelCheckpoint
+    args:
+      modelcp:
+        save_last: true
+        monitor: valid/BA
+        mode: max

runs/03_28_2025_02_03_04/config.yaml

@@ -0,0 +1,83 @@
+name: effb0-base-breakhis
+save_dir: runs
+trial_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_03_04
+save_cfg_path: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_03_04/config.yaml
+seed: 0
+data_type: BreakhisDataModule
+data:
+  data_source: /home/duong/Downloads/BreaKHis_v1/histology_slides/breast
+  batch_size: 32
+  shuffle: true
+  num_workers: 8
+  image_size:
+  - 224
+  - 224
+  aug:
+    RandomHorizontalFlip:
+      p: 0.2
+    RandomVerticalFlip:
+      p: 0.2
+    RandomRotation:
+      degrees:
+      - -5
+      - 5
+    ColorJitter:
+      brightness: 0.5
+      contrast: 0.5
+system_type: SimpleClassificationSystem
+system:
+  model_type: TimmModel
+  model:
+    model_name: efficientnet_b0
+    pretrained: true
+    num_classes: 1
+  optimizer:
+    name: Adam
+    args:
+      lr: 0.001
+  scheduler:
+    name: CosineAnnealingLR
+    args:
+      T_max: 300
+  loss:
+    name: BCEWithLogitsLoss
+  metrics:
+    metrics_names:
+    - BinaryAccuracy
+    metrics_short_names:
+    - BA
+train:
+  trainer:
+    accelerator: gpu
+    devices:
+    - 0
+    max_epochs: 300
+    check_val_every_n_epoch: 1
+    enable_progress_bar: true
+    accumulate_grad_batches: 1
+    log_every_n_steps: 50
+    default_root_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_03_04
+  logger:
+    names:
+    - WandbLogger
+    - CSVLogger
+    args:
+      wandb:
+        name: '03_28_2025_02_03_04'
+        project: histopath
+        save_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_03_04/wandb
+        id: '03_28_2025_02_03_04'
+        anonymous: false
+        log_model: all
+        entity: heartbeats
+      csv:
+        name: csv
+        save_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_03_04
+  callback:
+    names:
+    - ModelCheckpoint
+    args:
+      modelcp:
+        save_last: true
+        monitor: valid/BA
+        mode: max

runs/03_28_2025_02_14_37/config.yaml

@@ -0,0 +1,83 @@
+name: effb0-base-breakhis
+save_dir: runs
+trial_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_14_37
+save_cfg_path: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_14_37/config.yaml
+seed: 0
+data_type: BreakhisDataModule
+data:
+  data_source: /home/duong/Downloads/BreaKHis_v1/histology_slides/breast
+  batch_size: 32
+  shuffle: true
+  num_workers: 8
+  image_size:
+  - 224
+  - 224
+  aug:
+    RandomHorizontalFlip:
+      p: 0.2
+    RandomVerticalFlip:
+      p: 0.2
+    RandomRotation:
+      degrees:
+      - -5
+      - 5
+    ColorJitter:
+      brightness: 0.5
+      contrast: 0.5
+system_type: SimpleClassificationSystem
+system:
+  model_type: TimmModel
+  model:
+    model_name: efficientnet_b0
+    pretrained: true
+    num_classes: 1
+  optimizer:
+    name: Adam
+    args:
+      lr: 0.001
+  scheduler:
+    name: CosineAnnealingLR
+    args:
+      T_max: 300
+  loss:
+    name: BCEWithLogitsLoss
+  metrics:
+    metrics_names:
+    - BinaryAccuracy
+    metrics_short_names:
+    - BA
+train:
+  trainer:
+    accelerator: gpu
+    devices:
+    - 0
+    max_epochs: 300
+    check_val_every_n_epoch: 1
+    enable_progress_bar: true
+    accumulate_grad_batches: 1
+    log_every_n_steps: 50
+    default_root_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_14_37
+  logger:
+    names:
+    - WandbLogger
+    - CSVLogger
+    args:
+      wandb:
+        name: '03_28_2025_02_14_37'
+        project: histopath
+        save_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_14_37/wandb
+        id: '03_28_2025_02_14_37'
+        anonymous: false
+        log_model: all
+        entity: heartbeats
+      csv:
+        name: csv
+        save_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_14_37
+  callback:
+    names:
+    - ModelCheckpoint
+    args:
+      modelcp:
+        save_last: true
+        monitor: valid/BA
+        mode: max

runs/03_28_2025_02_15_38/config.yaml

@@ -0,0 +1,83 @@
+name: effb0-base-breakhis
+save_dir: runs
+trial_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_15_38
+save_cfg_path: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_15_38/config.yaml
+seed: 0
+data_type: BreakhisDataModule
+data:
+  data_source: /home/duong/Downloads/BreaKHis_v1/histology_slides/breast
+  batch_size: 32
+  shuffle: true
+  num_workers: 8
+  image_size:
+  - 224
+  - 224
+  aug:
+    RandomHorizontalFlip:
+      p: 0.2
+    RandomVerticalFlip:
+      p: 0.2
+    RandomRotation:
+      degrees:
+      - -5
+      - 5
+    ColorJitter:
+      brightness: 0.5
+      contrast: 0.5
+system_type: SimpleClassificationSystem
+system:
+  model_type: TimmModel
+  model:
+    model_name: efficientnet_b0
+    pretrained: true
+    num_classes: 1
+  optimizer:
+    name: Adam
+    args:
+      lr: 0.001
+  scheduler:
+    name: CosineAnnealingLR
+    args:
+      T_max: 300
+  loss:
+    name: BCEWithLogitsLoss
+  metrics:
+    metrics_names:
+    - BinaryAccuracy
+    metrics_short_names:
+    - BA
+train:
+  trainer:
+    accelerator: gpu
+    devices:
+    - 0
+    max_epochs: 300
+    check_val_every_n_epoch: 1
+    enable_progress_bar: true
+    accumulate_grad_batches: 1
+    log_every_n_steps: 50
+    default_root_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_15_38
+  logger:
+    names:
+    - WandbLogger
+    - CSVLogger
+    args:
+      wandb:
+        name: '03_28_2025_02_15_38'
+        project: histopath
+        save_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_15_38/wandb
+        id: '03_28_2025_02_15_38'
+        anonymous: false
+        log_model: all
+        entity: heartbeats
+      csv:
+        name: csv
+        save_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_15_38
+  callback:
+    names:
+    - ModelCheckpoint
+    args:
+      modelcp:
+        save_last: true
+        monitor: valid/BA
+        mode: max

runs/03_28_2025_02_17_13/config.yaml

@@ -0,0 +1,83 @@
+name: effb0-base-breakhis
+save_dir: runs
+trial_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_17_13
+save_cfg_path: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_17_13/config.yaml
+seed: 0
+data_type: BreakhisDataModule
+data:
+  data_source: /home/duong/Downloads/BreaKHis_v1/histology_slides/breast
+  batch_size: 32
+  shuffle: true
+  num_workers: 8
+  image_size:
+  - 224
+  - 224
+  aug:
+    RandomHorizontalFlip:
+      p: 0.2
+    RandomVerticalFlip:
+      p: 0.2
+    RandomRotation:
+      degrees:
+      - -5
+      - 5
+    ColorJitter:
+      brightness: 0.5
+      contrast: 0.5
+system_type: SimpleClassificationSystem
+system:
+  model_type: TimmModel
+  model:
+    model_name: efficientnet_b0
+    pretrained: true
+    num_classes: 1
+  optimizer:
+    name: Adam
+    args:
+      lr: 0.001
+  scheduler:
+    name: CosineAnnealingLR
+    args:
+      T_max: 300
+  loss:
+    name: BCEWithLogitsLoss
+  metrics:
+    metrics_names:
+    - BinaryAccuracy
+    metrics_short_names:
+    - BA
+train:
+  trainer:
+    accelerator: gpu
+    devices:
+    - 0
+    max_epochs: 300
+    check_val_every_n_epoch: 1
+    enable_progress_bar: true
+    accumulate_grad_batches: 1
+    log_every_n_steps: 50
+    default_root_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_17_13
+  logger:
+    names:
+    - WandbLogger
+    - CSVLogger
+    args:
+      wandb:
+        name: '03_28_2025_02_17_13'
+        project: histopath
+        save_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_17_13/wandb
+        id: '03_28_2025_02_17_13'
+        anonymous: false
+        log_model: all
+        entity: heartbeats
+      csv:
+        name: csv
+        save_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_17_13
+  callback:
+    names:
+    - ModelCheckpoint
+    args:
+      modelcp:
+        save_last: true
+        monitor: valid/BA
+        mode: max

runs/03_28_2025_02_22_37/config.yaml

@@ -0,0 +1,83 @@
+name: effb0-base-breakhis
+save_dir: runs
+trial_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_22_37
+save_cfg_path: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_22_37/config.yaml
+seed: 0
+data_type: BreakhisDataModule
+data:
+  data_source: /home/duong/Downloads/BreaKHis_v1/histology_slides/breast
+  batch_size: 32
+  shuffle: true
+  num_workers: 8
+  image_size:
+  - 224
+  - 224
+  aug:
+    RandomHorizontalFlip:
+      p: 0.2
+    RandomVerticalFlip:
+      p: 0.2
+    RandomRotation:
+      degrees:
+      - -5
+      - 5
+    ColorJitter:
+      brightness: 0.5
+      contrast: 0.5
+system_type: SimpleClassificationSystem
+system:
+  model_type: TimmModel
+  model:
+    model_name: efficientnet_b0
+    pretrained: true
+    num_classes: 1
+  optimizer:
+    name: Adam
+    args:
+      lr: 0.001
+  scheduler:
+    name: CosineAnnealingLR
+    args:
+      T_max: 300
+  loss:
+    name: BCEWithLogitsLoss
+  metrics:
+    metrics_names:
+    - BinaryAccuracy
+    metrics_short_names:
+    - BA
+train:
+  trainer:
+    accelerator: gpu
+    devices:
+    - 0
+    max_epochs: 300
+    check_val_every_n_epoch: 1
+    enable_progress_bar: true
+    accumulate_grad_batches: 1
+    log_every_n_steps: 50
+    default_root_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_22_37
+  logger:
+    names:
+    - WandbLogger
+    - CSVLogger
+    args:
+      wandb:
+        name: '03_28_2025_02_22_37'
+        project: histopath
+        save_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_22_37/wandb
+        id: '03_28_2025_02_22_37'
+        anonymous: false
+        log_model: all
+        entity: heartbeats
+      csv:
+        name: csv
+        save_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_22_37
+  callback:
+    names:
+    - ModelCheckpoint
+    args:
+      modelcp:
+        save_last: true
+        monitor: valid/BA
+        mode: max

runs/03_28_2025_02_31_16/config.yaml

@@ -0,0 +1,83 @@
+name: effb0-base-breakhis
+save_dir: runs
+trial_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_31_16
+save_cfg_path: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_31_16/config.yaml
+seed: 0
+data_type: BreakhisDataModule
+data:
+  data_source: /home/duong/Downloads/BreaKHis_v1/histology_slides/breast
+  batch_size: 32
+  shuffle: true
+  num_workers: 8
+  image_size:
+  - 224
+  - 224
+  aug:
+    RandomHorizontalFlip:
+      p: 0.2
+    RandomVerticalFlip:
+      p: 0.2
+    RandomRotation:
+      degrees:
+      - -5
+      - 5
+    ColorJitter:
+      brightness: 0.5
+      contrast: 0.5
+system_type: SimpleClassificationSystem
+system:
+  model_type: TimmModel
+  model:
+    model_name: efficientnet_b0
+    pretrained: true
+    num_classes: 1
+  optimizer:
+    name: Adam
+    args:
+      lr: 0.001
+  scheduler:
+    name: CosineAnnealingLR
+    args:
+      T_max: 300
+  loss:
+    name: BCEWithLogitsLoss
+  metrics:
+    metrics_names:
+    - BinaryAccuracy
+    metrics_short_names:
+    - BA
+train:
+  trainer:
+    accelerator: gpu
+    devices:
+    - 0
+    max_epochs: 300
+    check_val_every_n_epoch: 1
+    enable_progress_bar: true
+    accumulate_grad_batches: 1
+    log_every_n_steps: 50
+    default_root_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_31_16
+  logger:
+    names:
+    - WandbLogger
+    - CSVLogger
+    args:
+      wandb:
+        name: '03_28_2025_02_31_16'
+        project: histopath
+        save_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_31_16/wandb
+        id: '03_28_2025_02_31_16'
+        anonymous: false
+        log_model: all
+        entity: heartbeats
+      csv:
+        name: csv
+        save_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_31_16
+  callback:
+    names:
+    - ModelCheckpoint
+    args:
+      modelcp:
+        save_last: true
+        monitor: valid/BA
+        mode: max

runs/03_28_2025_02_36_29/config.yaml

@@ -0,0 +1,83 @@
+name: effb0-base-breakhis
+save_dir: runs
+trial_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_36_29
+save_cfg_path: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_36_29/config.yaml
+seed: 0
+data_type: BreakhisDataModule
+data:
+  data_source: /home/duong/Downloads/BreaKHis_v1/histology_slides/breast
+  batch_size: 32
+  shuffle: true
+  num_workers: 8
+  image_size:
+  - 224
+  - 224
+  aug:
+    RandomHorizontalFlip:
+      p: 0.2
+    RandomVerticalFlip:
+      p: 0.2
+    RandomRotation:
+      degrees:
+      - -5
+      - 5
+    ColorJitter:
+      brightness: 0.5
+      contrast: 0.5
+system_type: SimpleClassificationSystem
+system:
+  model_type: TimmModel
+  model:
+    model_name: efficientnet_b0
+    pretrained: true
+    num_classes: 1
+  optimizer:
+    name: Adam
+    args:
+      lr: 0.001
+  scheduler:
+    name: CosineAnnealingLR
+    args:
+      T_max: 300
+  loss:
+    name: BCEWithLogitsLoss
+  metrics:
+    metrics_names:
+    - BinaryAccuracy
+    metrics_short_names:
+    - BA
+train:
+  trainer:
+    accelerator: gpu
+    devices:
+    - 0
+    max_epochs: 300
+    check_val_every_n_epoch: 1
+    enable_progress_bar: true
+    accumulate_grad_batches: 1
+    log_every_n_steps: 50
+    default_root_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_36_29
+  logger:
+    names:
+    - WandbLogger
+    - CSVLogger
+    args:
+      wandb:
+        name: '03_28_2025_02_36_29'
+        project: histopath
+        save_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_36_29/wandb
+        id: '03_28_2025_02_36_29'
+        anonymous: false
+        log_model: all
+        entity: heartbeats
+      csv:
+        name: csv
+        save_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_36_29
+  callback:
+    names:
+    - ModelCheckpoint
+    args:
+      modelcp:
+        save_last: true
+        monitor: valid/BA
+        mode: max

runs/03_28_2025_02_40_09/config.yaml

@@ -0,0 +1,83 @@
+name: effb0-base-breakhis
+save_dir: runs
+trial_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_40_09
+save_cfg_path: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_40_09/config.yaml
+seed: 0
+data_type: BreakhisDataModule
+data:
+  data_source: /home/duong/Downloads/BreaKHis_v1/histology_slides/breast
+  batch_size: 32
+  shuffle: true
+  num_workers: 8
+  image_size:
+  - 224
+  - 224
+  aug:
+    RandomHorizontalFlip:
+      p: 0.2
+    RandomVerticalFlip:
+      p: 0.2
+    RandomRotation:
+      degrees:
+      - -5
+      - 5
+    ColorJitter:
+      brightness: 0.5
+      contrast: 0.5
+system_type: SimpleClassificationSystem
+system:
+  model_type: TimmModel
+  model:
+    model_name: efficientnet_b0
+    pretrained: true
+    num_classes: 1
+  optimizer:
+    name: Adam
+    args:
+      lr: 0.001
+  scheduler:
+    name: CosineAnnealingLR
+    args:
+      T_max: 300
+  loss:
+    name: BCEWithLogitsLoss
+  metrics:
+    metrics_names:
+    - BinaryAccuracy
+    metrics_short_names:
+    - BA
+train:
+  trainer:
+    accelerator: gpu
+    devices:
+    - 0
+    max_epochs: 300
+    check_val_every_n_epoch: 1
+    enable_progress_bar: true
+    accumulate_grad_batches: 1
+    log_every_n_steps: 50
+    default_root_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_40_09
+  logger:
+    names:
+    - WandbLogger
+    - CSVLogger
+    args:
+      wandb:
+        name: '03_28_2025_02_40_09'
+        project: histopath
+        save_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_40_09/wandb
+        id: '03_28_2025_02_40_09'
+        anonymous: false
+        log_model: all
+        entity: heartbeats
+      csv:
+        name: csv
+        save_dir: /home/duong/Github_repos/Histopathology_Project/runs/03_28_2025_02_40_09
+  callback:
+    names:
+    - ModelCheckpoint
+    args:
+      modelcp:
+        save_last: true
+        monitor: valid/BA
+        mode: max

system/__init__.py

@@ -0,0 +1,4 @@
+from typing import *
+
+from .base import BaseSystem
+from .simplecls import SimpleClassificationSystem